IMPORTANCE Human papillomavirus type 16 (HPV-16) is a major causative factor in oropharyngeal squamous cell carcinoma (OPSCC). The detection of primary OPSCC is often delayed owing to the challenging anatomy of the oropharynx. OBJECTIVE To investigate the feasibility of HPV-16 DNA detection in pretreatment and posttreatment plasma and saliva and its potential role as a marker of prognosis. DESIGN, SETTING, AND PARTICIPANTS This is a retrospective analysis of a prospectively collected cohort. Among a cohort of patients with oropharyngeal and unknown primary squamous cell carcinoma with known HPV-16 tumor status from the Johns Hopkins Medical Institutions and Greater Baltimore Medical Center (from 1999 through 2010), 93 patients were identified with a complete set of pretreatment and posttreatment plasma or saliva samples, of which 81 patients had HPV-16–positive tumors and 12 patients had HPV-16–negative tumors. Real-time quantitative polymerase chain reaction was used to detect HPV-16 E6 and E7 DNA in saliva and plasma samples. MAIN OUTCOMES AND MEASURES Main outcomes included sensitivity, specificity, negative predictive value of combined saliva and plasma pretreatment HPV-16 DNA status for detecting tumor HPV-16 status, as well as the association of posttreatment HPV DNA status with clinical outcomes, including recurrence-free survival and overall survival. RESULTS The median follow-up time was 49 months (range, 0.9–181.0 months). The sensitivity, specificity, negative predictive value, and positive predictive value of combined saliva and plasma pretreatment HPV-16 DNA status for detecting tumor HPV-16 status were 76%, 100%, 42%, and 100%, respectively. The sensitivities of pretreatment saliva or plasma alone were 52.8%and 67.3%, respectively. In a multivariable analysis, positive posttreatment saliva HPV status was associated with higher risk of recurrence (hazard ratio [HR], 10.7; 95% CI, 2.36–48.50) (P = .002). Overall survival was reduced among those with posttreatment HPV-positive status in saliva (HR, 25.9; 95% CI, 3.23–208.00) (P = .002) and those with HPV-positive status in either saliva or plasma but not among patients with HPV-positive status in plasma alone. The combined saliva and plasma posttreatment HPV-16 DNA status was 90.7%specific and 69.5%sensitive in predicting recurrence within 3 years. CONCLUSIONS AND RELEVANCE Using a combination of pretreatment plasma and saliva can increase the sensitivity of pretreatment HPV-16 status as a tool for screening patients with HPV-16–positive OPSCC. In addition, analysis of HPV-16 DNA in saliva and plasma after primary treatment may allow for early detection of recurrence in patients with HPV-16–positive OPSCC.

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ADF5 promotes stomatal closure by regulating actin filament dynamics, and members of the ABF/AREB transcription factor family may serve as potential upstream regulators of ADF5 in the drought stress/ABA signaling pathway.

BackgroundGenome-wide association studies and genomic predictions are thought to be optimized by using whole-genome sequence (WGS) data. However, sequencing thousands of individuals of interest is expensive. Imputation from SNP panels to WGS data is an attractive and less expensive approach to obtain WGS data. The aims of this study were to investigate the accuracy of imputation and to provide insight into the design and execution of genotype imputation.ResultsWe genotyped 450 chickens with a 600 K SNP array, and sequenced 24 key individuals by whole genome re-sequencing. Accuracy of imputation from putative 60 K and 600 K array data to WGS data was 0.620 and 0.812 for Beagle, and 0.810 and 0.914 for FImpute, respectively. By increasing the sequencing cost from 24X to 144X, the imputation accuracy increased from 0.525 to 0.698 for Beagle and from 0.654 to 0.823 for FImpute. With fixed sequence depth (12X), increasing the number of sequenced animals from 1 to 24, improved accuracy from 0.421 to 0.897 for FImpute and from 0.396 to 0.777 for Beagle. Using optimally selected key individuals resulted in a higher imputation accuracy compared with using randomly selected individuals as a reference population for re-sequencing. With fixed reference population size (24), imputation accuracy increased from 0.654 to 0.875 for FImpute and from 0.512 to 0.762 for Beagle as the sequencing depth increased from 1X to 12X. With a given total cost of genotyping, accuracy increased with the size of the reference population for FImpute, but the pattern was not valid for Beagle, which showed the highest accuracy at six fold coverage for the scenarios used in this study.ConclusionsIn conclusion, we comprehensively investigated the impacts of several key factors on genotype imputation. Generally, increasing sequencing cost gave a higher imputation accuracy. But with a fixed sequencing cost, the optimal imputation enhance the performance of WGP and GWAS. An optimal imputation strategy should take size of reference population, imputation algorithms, marker density, and population structure of the target population and methods to select key individuals into consideration comprehensively. This work sheds additional light on how to design and execute genotype imputation for livestock populations.Electronic supplementary materialThe online version of this article (10.1186/s40104-018-0241-5) contains supplementary material, which is available to authorized users.

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